{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/victor/.local/lib/python3.6/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use \"pip install psycopg2-binary\" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.\n",
      "  \"\"\")\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import math\n",
    "import json\n",
    "import time\n",
    "import itertools\n",
    "from scipy import stats\n",
    "import psycopg2 as psql\n",
    "from psycopg2.extras import RealDictCursor\n",
    "\n",
    "import sys\n",
    "sys.path.append(\"..\")\n",
    "from tools.flight_projection import *\n",
    "from tools.conflict_handling import *\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "\n",
    "try:\n",
    "    conn = psql.connect(\"dbname='thesisdata' user='postgres' host='localhost' password='postgres'\")\n",
    "except Exception as e:\n",
    "    print(\"Unable to connect to the database.\")\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "cur_read = conn.cursor(cursor_factory=RealDictCursor)\n",
    "cur_read.execute(\"SELECT * FROM public.ddr2_conflicts limit 20;\")\n",
    "batch = cur_read.fetchall()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AmJvIAuY1tveBRuNs7QBwJpEFnNXoDTc2GmdrB4AXElnAWa28/ApbOwAsgsgCFjR6zbU5b+3aRmMP3bSl8GwA+oPIAhq56JYdGbnggoUHTk4KLYCILKAFF++8t9nWDkILQGQBrWm6tUMmJ/PEre8qPyGAHiWygJY13dphemLCHlrA0BJZwKI03drhmfFxWzsAQ0lkAYuy8vIrGl9xaGsHYBiJLGDRLrplR/OtHW64ruxkAHqMyALa0lJo3Xh94dkA9A6RBbSt8R5aU1M5tPWm8hMC6AEiC+iIi3fem6xYsfDAEyds7QAMBZEFdMzYfXsajZuemMhX3/vuwrMB6C6RBXTU2P4HG4177sgRWzsAA01kAR3XNLRs7QAMMpEFFLFy45WNxrniEBhUIgsoYvSaa7N89eqFB05NCS1gIIksoJg1t9/Z7IrDqakcumlL+QkBLCGRBRQ1dt+eZntoTU664hAYKCILKO7infc2Ci1XHAKDRGQBS+Linfc2Gnd0/16hBQwEkQUsmdEbbmw0TmgBg0BkAUtm5eVXNN7awR5aQL8TWcCSGr3m2py3dm2jsW4mDfQzkQUsuYtu2dH4ZtK2dgD6lcgCuqLpzaQzOZknbn1X2ckAFCCygK4Z2/9gphuMm56YcCI80HdEFtBVv//qtzQKrW9+/GPF5wLQScu7PQFa874dP5eRkb//++np5Opb39e9CUGbHjvvtbn4paN5/XeOZuQs45771rElmxNAJziS1Uce2nlzRkZyxq+Hdt7c7alBW37zNf8sf3fOyrMe0Vr+3auWbD4AnSCy+sipqFroMegnLzvvnCTJB17/Y/OG1smM5GPL1+bRrxxd2skBtEFkAV31Mz9SPf/XH3j9j+WL549lKsn07K/vjCzP733PD2V85Zrse/jxfOhTf9atqQK0xDlZQFetXzeaP/+riRx47EiS5NOvvDyffuXl844/NW7zVZcsyfwAFsuRrD4yPT3za6HHoN9svuqSbHnbpY3HH3jsiCNaQM8TWX3k6lvf93xUnf7L1YUMgvXrRvPAbZuyrOE5hkIL6HW+LuwzN9/9gTz55FPdngYUs3/Hptxw9yOZanCE9sBjR/LYoSeza+uG8hMDaJEjWUDP2b+j+RGtiacn885dB4vOB2AxRBbQk/bv2JRzz2k29sSzU0IL6DkiC+hZ92/flAtedm6jsSeencq2+z5beEYAzYksoKft2rqhcWhNPD2Zt9/1iE1LgZ4gsoCet2vrhqxetaLR2OnEpqVATxBZQF+4Y8v6XPmm1Y3H2+IB6DaRBfSNzVdd0nJo3fPQHxecEcD8RBbQV07tDt/0xujjhyeEFtAVIgvoO+vXjeb9OzY1Pk9r/PBE3rPv0cKzAnghkQX0rTu2rG+8l9aRYyds8QAsKZEF9LX7t2/Kipc0+yibeHrSES1gyYgsoO/t3rax8V5ajmgBS0VkAQNh19YNLR3R+vF/87uFZwQMO5EFDIxWjmg9e3I677jnkcIzAoaZyAIGyq6tG7L2tRc0Gjt5MrnhbqEFlCGygIGz/erLGm9aOjUttIAyRBYwkDZfdUnjI1pT08n1biwNdJjIAgZWK0e0EjeWBjpLZAED7dRteJpyv0OgU0QWMPDWrxttKbTchgfoBJEFDIX160bzwG2bsqzhjaWPHDshtIC2iCxgqOzfsaml+x06RwtYLJEFDJ37t2/Ky17arLScowUslsgChtJv3PnWxrvDjx+ecL9DoGUiCxhau7ZuaBxaE09P5p27DpadEDBQRBYw1HZt3ZDVq1Y0Gnvi2SmhBTQmsoChd8eW9UIL6DiRBZDWQ8tteICFiCyAWa2EVjJzGx6hBcxHZAGcRmgBnSKyAF7kji3rs/a1FzQe78bSwFyWd3sCAL1o+9WX5dGvHM3+hx/PdIPxBx47kvob/yN3bFlffG60752fvjUZOe0eS9PT2f3DO7s3IQaSI1kA81i/bjTvv21T4/Hud9gfng+sF/1656dv7fbUGDAiC2ABbiw9YE6F1UKPQZtEFkAD+3dsarw7/JFjJ+ylBYgsgKZ2bd2QFS9p9rFp01JAZAG0YPe2jTn3nGZjhVaPmp6e+bXQY9AmkQXQovu3b3JEq4/t/uGdfx9Vp/1ydSGdZgsHgEXYvW1jtt332Uw8Pbng2FOhtXvbxvIToxFBxVJo+0hWVVXnVVW1p6qqJ6qq+tOqqvZ2YmIAvW7X1g2NNy098exUbrj7kcIzAnpJJ45k/XKSZ5KM1XU9XVXVKzvwmgB9YfvVl+Weh/4444cnFhw7NZ1cf9cj2fK2S7N+3egSzI5O+uov/fgZj51/44NLPxH6RltHsqqqenmSn03y/9R1PZ0kdV3/bScmBtAvtl99mdvwDLin9l7X0uOQJCPTbVxNUVXVDyT5+OyvK5N8O8l76rr+XIOnvy7J1xb9mwP0mD2//aV84tHDjcf/8/WvzU0/8caCM6JT5jqKdcqaX/jYEs6EHvD6JF9vMrDdrwvPSbImyWN1XW+vquofJ3m4qqrvr+v6eJMXOHbs25maemHoXXjh+XnyyafanNpgsjZzsy7zszZzK7EuP/GW78urXvGyxvc7/MSjh/OqV7ysp7469H5p3bCv17C8Z5YtG8mqVS9v7Tlt/p7fSPJckoeSpK7r/5rkm0nG2nxdgL506n6HTW/Ds+/hx/PoV46WnRTQFW1FVl3X30xyIMmPJElVVWNJvifJn7c/NYD+tX9H8xtL73v48dzz0B8XnA3QDZ3YjPTnk7y7qqo/TfIbSTbXdb3wZTYAA+6B2zY13h1+/PCE0Oph811F6OpCzqbtLRzquv5qko3tTwVg8Ny/fVPecc8jmTy58NhTobX96svKT4yWrfmFjw3FuUd0jtvqABR2/3ZHtGAYiSyAJdBqaL1n36NlJwQUJ7IAlkgroXXk2Ak3loY+J7IAltD92zflgped22jsiWensu2+zxaeEVCKyAJYYru2bmgcWhNPTzpHC/qUyALogl1bN2TFS5p9BI8fnnBEC/qQyALokt3bNjYOrYmnJ3P9XY8UnhHQSSILoIt2b9vY+KvDJEIL+ojIAuiyXVs35Mo3rW483lWH0B9EFkAP2HzVJY1Dy1WH0B9EFkCP2HzVJVn72gsajZ14etIRLehxIgugh2y/+rJseduljcaeeHYq19/1SB79ytHCswIWQ2QB9Jj160bzwG2bGo/f9/DjQgt6kMgC6FFNj2glM6EF9BaRBdCj1q8bzZa3XZqRkWbjfXUIvUVkAfSw9etG8/4dmxpvWuqrQ+gdIgugD+zetjHnntNsrNCC3iCyAPrE/dtbOxnejaWhu0QWQB954LZNWdbwHK3xwxNCC7pIZAH0mf07NjX+6lBoQfeILIA+dP/21kLLbXhg6YksgD51//ZNueBl5zYaO/H0pCNasMREFkAf27V1Q+P7HY4fnsiHPvVnhWcEnCKyAPrc9qsvaxxaBx47kvfse7TwjIBEZAEMhO1XX5bVq1Y0Gnvk2AnnaMESEFkAA+KOLesbH9GaeHoy79x1sOyEYMiJLIAB0spXhyeenco77nmk8IxgeIksgAHTyleHkyfjiBYUIrIABtAdW9bnyjetbjT2xLNTToaHAkQWwIDafNUljUPryLET9tGCDhNZAANs81WXNP7qcPzwRK79d/+l8IxgeIgsgAF3x5b1jUPrW0896xwt6BCRBTAEWj1HS2hB+0QWwJDYfNUl2fK2SxuNPfHsVK6/y/YO0A6RBTBE1q8bzZa3XZrl54w0Gn/D3UILFktkAQyZ9etGs3f7lY3GTk0LLVgskQUwpJp+dTg1HV8dwiKILIAhtX7daOOT4ZO4BQ+0SGQBDLFWToafPJlsu++zhWcEg0NkAQy59etG88BtmxqNnXh60vYO0JDIAiBJ83O0Tm3v8OhXjhaeEfQ3kQVAkpkjWrf8zGWNx+97+HGhBWchsgB43sY3vyYP3LYp557TbLzQgvmJLADOcP/2TbngZec2Giu0YG4iC4A57dq6ISte0uxfE0ILziSyAJjX7m0bWzqi9aFP/VnhGUH/EFkAnFUrR7QOPHZEaMEskQXAgnZv29j4ZHihBTNEFgCN3L+9+VWHQgtEFgAtEFrQnMgCoCX3b9/U0jlarjpkWIksAFrWylWHH/jEeOHZQG8SWQAsyq6tG7J61YoFxz13ctrXhgwlkQXAot2xZX2jrw4PPHYkP7/zgK8OGSoiC4C27N62sVFoPfvctA1LGSoiC4C27d62sdFXh4mrDhkeIguAjrhjy/qsfe0FjcYeeOxI7nnojwvPCLpLZAHQMduvvixXvml1o7HjhyeEFgNNZAHQUZuvuqSl0PLVIYNKZAHQcZuvuqTxPlrO0WJQiSwAiti1dYNb8DDURBYAxdy/fVNLR7Tso8UgEVkAFLVr64bGofXrn6wLzwaWjsgCoLimofWdyZPZeu9nHNFiIIgsAJZE09B6+pmTdoZnIIgsAJZMK18dOhmefieyAFhSu7ZuaOkWPL46pF+JLACW3B1b1jfesNTJ8PQrkQVAV2y+6pJsedulC477zuTJJZgNdJ7IAqBr1q8bbXxTaeg3y7s9AQCG2/arL8u2+z6biacn5x1z/V2PPP/XV75pdTZfdclSTA3a4kgWAF3X6lWH9zz0x4VnBO0TWQD0hF1bN+TKN63OspGFx44fnnDVIT3P14UA9IzNV13y/FeBp39FOJd9Dz+eZOa8LuhFjmQB0Lf2Pfy4I1r0LJEFQE9qetXh/tkjWtBrRBYAPWn71Zc1Ohl+Osm2+z5bfkLQIpEFQM/atXVDoyNaE09P5j37Hl2CGUFzIguAntb0iNaRYydy/V2PuKk0PUNkAdDzdm3dkBUvafavrAOPHRFa9ASRBUBf2L1tY0uh5apDuk1kAdA3dm/b2Hhn+H0PP25neLpKZAHQV3Zt3ZDVq1Y0Gjt+eEJo0TUiC4C+c8eW9Y2/Ohw/POEcLbpCZAHQl3Zv29j4iJaT4ekGkQVA37pjy3qhRc8SWQD0tVa+OhRaLCWRBUDfa+WqQ9s7sFREFgADYdfWDS1t7wCliSwABsaurRty7jnNxr7jnkfKToahJ7IAGCj3b9/U6BytyZPJtvs+uwQzYliJLAAGTtNb8Ew8PelEeIoRWQAMpN3bNmbZyMLjDjx2pPxkGEoiC4CBtX/Hpkah5dY7lCCyABho+3dsWnDM+OEJ2zrQcSILgIG35W2XLjjGtg50msgCYOCtXzeaK9+0esFx79x1sPxkGBoiC4ChsPmqS3LOAudnnXh2ytWGdIzIAmBoXP/Whb82dLUhnSKyABga69eNZvWqFQuOc7UhnSCyABgqd2xZv+CY8cMTSzATBp3IAmDoNLna0JYOtEtkATB0mnxt+P7fGxdatEVkATCU7tiy/qz3N5yans4HPjG+hDNi0IgsAIbW7m0bs/a1F8z78+dOTjsJnkUTWQAMte1XX3bWn48fnrB3FovSsciqqurfVlU1XVXVP+zUawJAL7B3FovRkciqquqyJJcnOdyJ1wOApdTkljsHv/iXSzATBknbkVVV1UuT7E5yU/vTAYCl1+SWO+/7zS8tzWQYGJ04knV7kg/Xdf31DrwWAHTFQrfcmXzOfQ1pzfJ2nlxV1fok/yjJbYt9jVWrXj7n4xdeeP5iX3LgWZu5WZf5WZu5WZe5Deu6/IuN5+e/jf9t/r8/PzbvmINfOpJt1/zgEs6qPwzre2YhbUVWkrckWZvka1VVJcmrk3yqqqqfq+v695u8wLFj387U1PQLHrvwwvPz5JNPtTm1wWRt5mZd5mdt5mZd5jbs6/Kvf+IHsuXuR3Jyeu6fT09nqNdnLsPynlm2bGTeA0PzaSuy6rq+K8ldp/6+qqqvJ3lrXddfbud1AaBbrn/rpdn38OPdngYDwD5ZAHCa9etG5z0J/iXLFzg7Hk7T0ciq6/p1jmIB0O+uf+uleXFOjSS59kfXdmM69Kl2z8kCgIGzft1okuTjn/mLHDv+naxa+dJc99Z1WXfR/LfggRcTWQAwh/XrRp+PrWR4TvCmc5yTBQBQgMgCAChAZAEAFCCyAAAKEFkAAAWILACAAkQWAEABIgsAoACRBQBQgMgCAChAZAEAFCCyAAAKEFkAAAWILACAAkTLupdYAAAK90lEQVQWAEABIgsAoACRBQBQgMgCAChAZAEAFCCyAAAKEFkAAAWILACAAkQWAEABIgsAoACRBQBQgMgCAChAZAEAFCCyAAAKEFkAAAWILACAAkQWAEABIgsAoACRBQBQgMgCAChAZAEAFCCyAAAKEFkAAAUs7/YEAGCxPrrr5jMe+6lt7+vCTOBMjmQB0JfmCqyzPQ5LTWQBABQgsgAAChBZAAAFiCwAgAJEFgB9ab6rCF1dSK+whQMAfUtQ0cscyQIAKEBkAQAUILIAAAoQWQAABYgsAIACRBYAQAEiCwCgAJEFAFCAyAIAKEBkAQAUILIAAAoQWQAABYgsAIACRBYAQAEiCwCgAJEFAFCAyAIAKEBkAQAUILIAAAoQWQAABYgsAIACRBYAQAEiCwCgAJEFAFCAyAIAKEBkAQAUILIAAAoQWQAABYgsAIACRBYAQAEiCwCgAJEFAFDA8m5PAACgVU/tve6Mx86/8cEln8fZOJIFAPSVuQLrbI93i8gCAChAZAEAFCCyAAAKEFkAAAWILACgr8x3FWGvXV1oCwcAoO/0WlDNxZEsAIACRBYAQAEiCwCgAJEFAFCAyAIAKEBkAQAUILIAAAoQWQAABYgsAIACRBYAQAEiCwCgAJEFAFCAyAIAKEBkAQAUILIAAAoQWQAABYgsAIACRBYAQAEiCwCgAJEFAFDA8naeXFXVqiQfSvJ9SZ5N8kSSd9R1/WQH5gYA0LfaPZI1neSX67qu6rp+Q5K/SHJX+9MCAOhvbR3Jquv6W0kOnvbQF5Lc1M5rAgAMgpHp6emOvFBVVcuS/H6S363r+n0NnvK6JF/ryG8OALA0Xp/k600GtnUk60XuS/LtJL/WypOOHft2pqZeGHoXXnh+nnzyqQ5ObXBYm7lZl/lZm7lZl7lZl/lZm7kNy7osWzaSVate3tJzOhJZVVXtTHJxkrfVdT3VidcEAOhnbUdWVVV3Jnlzkv+truvvtD8lAID+1+4WDuuS/N9JDiX5fFVVSfK1uq7/ZQfmBgDQt9q9uvArSUY6NBcAgIFhx3cAgAJEFgBAASILAKAAkQUAUIDIAgAoQGQBABQgsgAAChBZAAAFiCwAgAJEFgBAASILAKAAkQUAUIDIAgAoQGQBABQgsgAAChBZAAAFiCwAgAJEFgBAASILAKAAkQUAUIDIAgAoQGQBABQgsgAAChBZAAAFiCwAgAJEFgBAASILAKAAkQUAUIDIAgAoQGQBABQgsgAAChBZAAAFiCwAgAJEFgBAASILAKAAkQUAUIDIAgAoQGQBABQgsgAAChBZAAAFiCwAgAJEFgBAASILAKAAkQUAUMDybk8AABgcH9118xmP/dS293VhJt3nSBYA0BFzBdbZHh90IgsAoACRBQBQgMgCAChAZAEAFCCyAICOmO8qwmG9utAWDgBAxwxrUM3FkSwAgAJEFgBAASILAKAAkQUAUIDIAgAoQGQBABQgsgAAChBZAAAFiCwAgAJEFgBAASILAKAAkQUAUIDIAgAoQGQBABQgsgAAChBZAAAFiCwAgAJEFgBAASILAKAAkQUAUIDIAgAoYHkXf+9zkmTZspE5fzjf41ib+ViX+VmbuVmXuVmX+VmbuQ3Dupz2Zzyn6XNGpqeny8xmYf8kyWe79ZsDACzChiSfazKwm5H10iQ/mORvkpzs1iQAABo4J8n3JvmjJN9p8oRuRhYAwMBy4jsAQAEiCwCgAJEFAFCAyAIAKEBkAQAUILIAAAoQWQAABRS/rU5VVV9P8szsryTZUdf1p6qqujzJ/UlWJPl6kmvquv67OZ6/O8k/zczGX99O8q/ruv7vsz87mOSiJMdnh/9qXdcfKPVn6aQOrMuDSX44yTdnH/qtuq5/afZnr0zyoSSvS3IiyY11Xf/XQn+UjurAunw6yStm/3Z5knVJfqCu6z8525r1g7OszUeSXJmZTfLOr+v62/M8/x8k+UCSNyd5LsmtdV3/3kI/63UdWJeB/IxJOrI2D2a4PmearstAfs7MtS5JvpaZz97vzcxnwx8l+T/quj4xx/PnfU/08/ulHUt178KfqOv6y6f+pqqqZUk+nOS6uq4/V1XVe5LcleT6OZ77X5K8q67ryaqq3prko0m+77Sf39wv/zKYQzvrkiR31XX9a3M8/u+T/EFd1/+sqqp/kuTDVVWN1XXdLzvPLnpd6rr+4dOe92NJ7qjr+k9OGzLfmvWLF6zNrPcn+b+S/O0Cz701yfG6rr+/qqqLk3y2qqrvn/0Xydl+1g/aWZdB/oxJ2lubZEg+Z2Y1WpcB/5x58efv65Jsq+v6sdnP4ocy83nxi3M892zviX5/vyxKt74ufHOSZ+q6PnXvn/+Y5CfnGljX9e/VdT05+7ePJnn17P/Rg6jxuizgJ2efm9nX+k6Sf9SRGXbHYtfl+iQPFJtVj6jr+pG5jurN4acy81+kqev6iST/PcmPNvhZX2q6LkP2GZOkpffM2Qza58xi12WgP2fquv56XdePzf71VJL/luS18ww/23ti4N4vTSzVB8lHqqr6k6qq/kNVVRdk5vD74VM/rOv6m0mWVVX13Qu8zv+Z5D/P/h99yj1VVf1pVVUfrqrqVZ2felHtrsu22T/771RVtTZJqqpalWRk9rmnfCPJawr9GUpo+/1SVdVoZg7Zf+hFPzpjzfrMi9emFS9Yx7zwfXG2n/WDdtbldIP2GZO0vzbD8jnTsgH9nJl3XaqqWpGZqPzdFz/pbO+JAXm/LMpSRNaGuq5/IDM3gx5JsqhDqFVV/XSSn0ly02kPb67rem2SNyb5s8wc5u8X7a7LLyT5/rqu35Dk40k+WVXVOR2eYzd05P2S5GeTfLKu6ydPe6zf16xTazNofMbMz+fM3HzOzG3edamqanmS30jySF3XZ0QWcyseWXVd/+Xs/34nyX9I8kOZKdjnDzdWVfWKJFN1XX9rrteoqupfJvmlJFfVdf38d+WnvfbJJL+a5PJ+Oczf7rrUdf3Xp/5ru67rX0/y8iSvruv62GnPPeWiJH9Z6I/SUZ14v8z6ubzoEP58a9bRP0BB86xNK16wjnnh++JsP+tpHViXgfyMSdpfmyH7nFmMgfqcmW9dZiPxI0n+R5Kb53nuvO+Jfn+/tKPoh0VVVS+rquq7Zv96JMlPJ/lSki8mWTF78luS/HyS35rnNd6aZFdmPvy+ftrjy2evVjjl6iR/+qLD/D2pQ+vyqtP++qokJ5P89exDvzX73My+1orZ1+5pnViX2edekeS7MnNC8+mPn23NetpZ1qYVv5XkHbOvcXFm/mv1kw1+1rM6sS6D+BmTdGxthulzptXXGajPmfnWZfY/Kh7MzJ/j7QucqH6290Rfvl/aVfrqwlcm+dhsBZ+T5PHMXPo5VVXV5iT3V1V1XmYvyT/1pKqqvpTkn9d1fSQzl5U/m+S3q6o6NeSfZuYS0/9cVdVLMnNY868z86boB51Ylw/O/gtgKjOXl/+Luq6fmx16W2au3Lg2M5fKbu6TfzF0Yl2Smf+6/PXZow+nO9ua9bo51yZJqqr6eJL/dXZcXVXVl+u6vmr2Z6evzT1JHqyq6s8z84F5Y13XT80+72w/62WdWJdB/IxJOrM2Q/M5k7S0Lsngfc7Mty4/mpnP2y8n+eLsPyN/WNf1O6uqWp3kE3Vdv3H2Nc72nujX90tbRqanB/rqSQCAruibcwsAAPqJyAIAKEBkAQAUILIAAAoQWQAABYgsAIACRBYAQAEiCwCggP8f51pPVm4NIwQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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e3+dRzSzcudCRqes/dXffxwHA4RFSjKwHLn9nfnDnna33X3Pu+Yc88qWfrnjzC+f9+a5Hdg9oJADUElIsaZ0uKF/oQvNt121sH1ETEwOPqL2OWG51coBhZvkDlrxu787buXlTdn761lb7tnnkSz+d89J1+563N5fbv7qt1UONAVgcjkgxUrZdt3HmmqgWjlq3blEjKpn/YcVJ8uFPtD81CcDgOSLFyBjUauWDtHuP1csBljJHpBgJ3UbUM9/zB30eEQDjwBEploTr33NhJva77np6Ojn74ve2em03q5Uv9jVRc1n/nLW5dUvnNa6uvfmubDjzpAGOCIC2HJFi0e2NqIN/Xf+eCxd87d0XnNc6oiaOPXbJRVSSBSNpvsgCYHEJKRbd3nBaaNvB7r7gvOSxx1p9xlHr1i3p03nLrIIAMJSEFEPp7jdf0Dqi1px7/pK/sPx1Lzt5sYcAQAUhxVDZuXlT7j73te1O5y3iQpvdWmgZhHdf/8UBjQSAbrjYnEU3PXuH/8EXm08fdOf/zs2bWq8RlSQnXvXhHoxuabjzG+3uSARgsByRYtGdffF794XT/r/2v2uv24hac27/HzwMAI5IsSTMt9TBtus2tn7kS5KsPGP9UJzOO9gTj5jMIz+cWuxhANAFR6RY0moias2rz+njiPrnyovOmPfnF73vM4MZCACtOSLFknXvpZdk99aWayhNTGTN688byiNRbT34cLu7FAEYHCHFktRVRGW0LiwHYHg4tceS88Dl72wfUZOTOfGD1/R1PIO07qeOXewhANAFIcWScu+ll+QHd97Zat+j1q3LiR+4us8jGqy3nn3qvD9/+1W3D2gkALTh1B5Lws7Nm7LtQ1cdunhUB8N8Ufnh2Lqj3XMFk+ShD7z2kG0rzr+md4MBQEjRW1/41A2598u3Z3p6KhMTk3n6s07Lc1/8ynlf0+2deUetWzfSEXXE8on8cHe7oOxkrojau11MAfSOU3v0zBc+dUPu+bvPZXp6Zi2k6emp3PN3n8sXPnVDx9d0G1HD8Ny8w3XOS9ct9hAAaElI0RPvv+y2fP1vN835s3u/PPd1PQ9c/s6uI2qUlzfYy3P3AIaHU3sctvdfdtvs7+Y+HbX3CNX+vnbxWzL9YMvnxy1bljW/8vqxiKg2PHcPYOkQUvTQROaKqYmJAw98dhNRy9euzdN/6/d6MTgA6Dmn9uiZR6eOn/Omu6c/67R9v3/g8ne2jqij1q0b24ha/5y1h/X6TheUu9AcoLcckaJn/mnPzBpIR07en5kjUxM54Weev++uvW3XbWy9RtTytWtH/qLy+Ww486TcuqXzoqTX3nxXNpx50rzvIZoA+k9I0ZXHr4ea2z/tOXVfUCXJc198epLu7s6bOPbYsT0S1datW7YuGFIA9J+QorWFIupgF7yt+4g6at26sT4SBcBwEVL0xN5oOlg3ETXup/MO1ouFOQHoLxeb0zc7N2/qKqKczjvQQgtzXnvzXQMaCQCdCCn6ZtuHP9Rqv5VnrBdRc1hoYc75LkYHYDCEFH1x76WXJHv2LLjfqD83D4DRJqRordN1UAdvv/fSS7J768JHS1xYDsCwc7E5XekUU3u1XbV85RnrHYlq4byXn5yrbrqj489v/+q2BU8BAtA/jkjRM20jyum89haKpI98sgxoJADMRUjRE20f/WKJg9569LGFr0MDoH+EFIet7aNfLHEAwKhZ8BqppmlWJbk2yTOS/DDJ15K8oZSyvc9jYwi0XStKRNVb/5y18y514DopgMXT5ojUdJJ3lVKaUsqzktyT5LL+Doth8Z0//7MF9/HsvMOz0DP1XCcFsHgWPCJVSvlekk/vt2lzkgv6NSCGy9SuXQvu88z3/MEARjK+XCcFsHi6ukaqaZrJzETUX/RnOIyaNeeev9hDGAnLJhZ7BADMpdt1pN6XZFeSP+rmRatWHXPIttWrV3T50cxnsebznhXHZM9Dcx+VWvnPn5VnvPzMAY+oN5ban8+3nH1qLv+zL3b8+VcfeDBn/OxTBzii7iy1+Rxm5rK3zGdvjeN8tg6ppmnek+SZSV5eSpnq5kN27NiVqanHn2K/evWKbN/+UDdvwTwGPZ87N2/Kd2/8eHZ/b0cmjj46mZhIpqcP2Oeodeuy5sJfG8r/nZfin89TnnbsvD//o4/97YL7LJalOJ/Dylz2lvnsrVGYz8nJiTkP/synVUg1TfN7SX42yb8qpTxaMTZGwM7Nm/Lt6z+a6Ycf3rdt+uGHk2XLMvnEJ2Zq164sf9KqPPmsV2Tl856/iCMdP66TAlgcbZY/OCXJbya5O8mmpmmS5L5Syr/p89hYQnZu3pRtV38wmZrjYOSePZk84sic8MGuzvjSpWUTyZ7phfcDYHDa3LX31SQudR1z2665eu6ImrX7ezsGOJrx9LqXzf/cvcPx0Adee8i2Fedf05fPAhglVjZnQduu25js3j3vPsuftGpAoxlf/Vp0c66Imm87AI8TUsxr23UbF1y5fOKII/Lks14xoBEBwNIhpOio7eNfjnvNa11cPiDrn7N2zu0TmXlUDACDJaToqM3jX1aesV5EDdCGM0/KEcsPvWRxOsmNt90z+AEBjDkhxZy2Xbdxwce/HLVuXda8+pwBjYi9frh77lv3duy0MgnAoAkpDtHmlN7KM9bnab/2GwMaEftbtfLIjj+rOb3X6e48d+0BLKzbR8QwBhY6pbfyjPWORC2is05/RsdlED78iTur7u4TTQB1HJHiADs3b5r3lN7E0UeLqEU2XyjttmInwEAJKQ6w0NGo485+1YBGAgBLn5Bin4WORrlDDwAOJKTY59vXbuz4M6f0lpZl8zy06dqb7xrcQADGnJAiyczRqOlHO98+75Te0vK6l53c8We3fWnrAEcCMN6EFNm5eVO2Xf3BefdxSm9pme+C8ynXmwMMjJAaczs3b8q2D1+dTE113Gfi6KMHOCLampzn9J7HxQAMhpAac9++dmOyZ/e8+zittzSd/uy5n7uXJNd/6u4BjgRgfAmpMbbtuo3zXheVuFNvKdtw5kkdf7brkfnjGIDesLL5mGrzGJg1554vogBgHo5IjamFFt5MXGA+DI4+alnHn7lOCqD/hNSYmm/hzcQF5sPiP/xi0/FnH/lkGeBIAMaTkOJQExMuMB8S8y2D8OhjewY4EoDx5BqpMbNz86Z8+/qPzrvPmtef57QeALTgiNQY2bl5U7Z96KpMP/zw3DssW+YC8xHjcTEA/SWkxsh3/vzPkukOy15PTmbNr7xeRA2h9c/pvJ7UrVu2uugcoI+E1BiZ9wLzqSkRNaTmW08qSa666Y687rJbHJ0C6AMhRZJk+ZNWLfYQOAyrVh654D63btkqpgB6TEiNkfmWNHjyWa8Y4EjotbNOf0ar/W770tY+jwRgvAipMXLc2a9Klh26gKPHwAy/005ZkyOWz/MU41lTHS6RA6CO5Q/GyN5Y+u6NH8/u7+3I8ietypPPeoWIGhHnvHRdrv7LO7JnnliamEje+sefy46dj2bVyiNz1unPmHctKgDmJ6TGzMrnPV84jai9QXT9p+7u/NDi6WTHzpkHVe/Y+WiuuumOfP0fHlzwgnUA5iakYIScdsqanHbKmtz+1W35yCfLAaubH7F8Ij/cfejhqlu3zFw3JaYAuiekYATtDar9ve6yWzruf+uWrTnhKcc6zQfQJSHVZ++/7LZDtl3wttMXYSSMu1Urj9x3Wm8uN952j5AC6JK79vporoiabzv000JLJMwXWQDMTUjBmDjtlDXzPk6mzaKeABxISMEY2XDmSXPG1BHLJ1sv6gnA44QUjJkNZ56U815+8r4jUKtWHplzXnqS66MAKrjYHMbQXHf1AdA9R6T6qNPdee7aA4DR4IhUn4kmABhdjkgBAFQSUgAAlYQUAEAlIQUAUElIAQBUElIAAJWEFABAJSEFAFBJSAEAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBUElIAAJWEFABAJSEFAFBJSAEAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBUElIAAJWEFABAJSEFAFBJSAEAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBUElIAAJWEFABAJSEFAFBJSAEAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBUWt5mp6ZpTkyyMcmqJDuSvKaU8rV+DgwAYKlre0TqT5JcWUo5McmVSf60f0MCABgOC4ZU0zQ/nuTUJNfPbro+yalN06zu58AAAJa6Nkeknprkm6WUPUky+59bZ7cDAIytVtdIHa5Vq445ZNvq1SsG8dFjw3z2lvnsLfPZO+ayt8xnb43jfLYJqb9P8pNN0ywrpexpmmZZkrWz21vZsWNXpqam9/3z6tUrsn37Q10PlrmZz94yn71lPnvHXPaW+eytUZjPycmJOQ/+zPuahXYopXwnyZeSnD276ewkW0op27seIQDACGl7au+NSTY2TXNpku8neU3/hgQAMBxahVQp5a4kP9/nsQAADBUrmwMAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBUElIAAJWEFABAJSEFAFBJSAEAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBUElIAAJWEFABAJSEFAFBJSAEAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBUElIAAJWEFABAJSEFAFBJSAEAVBJSAACVhBQAQCUhBQBQSUgBAFQSUgAAlZYv9gAARsVDH3jtIdtWnH/NwMcBDI4jUgA9MFdEzbcdGA1CCgCgkpACAKgkpAAAKgkpAIBKQgqgBzrdneeuPRhtlj8A6BHRBOPHESkAgEpCCgCgkpACAKgkpAAAKgkpAIBKQgoAoJKQAgCoJKQAACoJKQCASkIKAKCSkAIAqCSkAAAqCSkAgEpCCgCgkpACAKgkpAAAKgkpAIBKQgoAoJKQAgCotLzP778sSSYnJw75wVzbqGc+e8t89pb57B1z2Vvms7eGfT73G/+ytq+ZmJ6e7s9oZrwgyWf6+QEAAD32wiSfbbNjv0PqyCQ/l+RbSfb084MAAA7TsiQ/keTzSR5t84J+hxQAwMhysTkAQCUhBQBQSUgBAFQSUgAAlYQUAEAlIQUAUElIAQBU6ukjYpqmuT/JD2Z/JclvlFJubprmo0nWZ2aRqxWllF0dXn9Nkhcn+e7spo+VUn63l2McJnPNZ5L7kvxpZuZyd2YWDfvVUsojc7z+uCTXJjk+ySNJzi+l/HW/x71U9WA+P53kaUl2zm76w1LKh/s66CWqw1z+nySfS/Ijs9u+leSNpZT753j9jyT5cJKfzcy8X1xK+cu+DnoJ68F8XhPfnft0+rtov59fneRX0uHvI9+dB+rBfH46I/zd2Y9n7f3bUspXDtr2oST/Kcm3W7z+slLKH/V+WEPrgPlsmub4JBeVUrY0TTOZ5PokFyf57Tle+/tJ/m8p5SVN07wgyXVN05xYShnnVVgPZz6T5MJx/gv/IIf8u940zb8spfzj7O//Y5Irkpw1x2svTrKzlHJC0zTPTPKZpmlO6PR/ssbE4cxn4rvzYHP9XZSmaV6eZKHvQN+dhzqc+UxG+LtzIKf2Sim3lFK+M4jPGnWllPtLKVtmfz+V5P8l+akOu/9ykj+Z3fezmVnu/rmDGOew6HI+WcDev/RnrUwy1WHXV2bmSGBKKV9L8oUkL+3v6IZPF/NJC03TrEryjiQXLbCr784WupjPkdaPI1IfbZpmIjMP+7uklPJgl6+/qGmaNyS5J8lvllLu7PkIh0vH+Wya5olJXpfkNw9+0ewf8IlSynf32/xAkqdm5vTVuKqaz/28u2ma30/yt5k5vP3Nvo52aZtzLpum+USSUzNzmuklHV77tCTf2O+f9/7ZHGeHM5+J786DzTWfVyZ5RynlH5ummfNFvjs7qprP/Yzsd2evj0i9sJTyM5l5UPFEkm4PM//nJCeUUp6V5MYkn2yaZlmPxzhMOs5n0zTLk/x5kltKKX+xSOMbNocgxErMAAACaElEQVQ7nxtKKeuSPDvJXUlu6PN4l7KOc1lK+aUkazNzmvTtizO8oXO48+m780CHzGfTNL+c5IellL9a3KENpcOdz5H+7uxpSJVS/n72Px9N8sdJfqHL139z9vRKSikfSXJMkqf0cozDpNN8zn5BfjTJ95Nc2OG1O2b3ffJ+m5+W5O/7OOQl7XDm86DX70nyh0meN3td1dhZ6N/12X+PP5RkQ4e3eCAHnkL1ZzP18+m780Ad5vOMJC9qmub+2Yunk+SrTdOcfNBrfXce5HDm86DXj+R3Z8/+izRNc3TTND86+/uJJP8+yZe6fI+f3O/3ZybZk2RkDv91o9N8zv7huyYzc/P6BS5+/FiSN86+xwuSPDHJ3/Rz3EvV4c5n0zTLZ+/k2evsJF/e+5fXOJlnLlcf9JfPv0vy5Q5v87Ekb5h9j2dm5v/pfrJ/o166ejGfvjsf12k+Sym/Wkp5Sinl+FLK8bO7n1JKuWOOt/HdOetw53Mcvjt7eY3UcUk+Pvv/7pcluSPJryZJ0zQ3JvkXs/uVpmm+Uko5c/ZnX0ryS6WUrUk2zk74VGZuk/zXpZTdPRzjMOk0ny9N8uokX0nyN7PnpT9XSnlT0zRrk3yilPLs2fd4W2buNjknM7fwbhilP7xdOtz5PDLJXzVNc0RmDm1/MzNfKOOo01yuSXJN0zRPyMwc3ZeZuU1yyL/r757d9+uZ+Uv//FLKQ4P9r7Fk9GI+fXc+ruPfRZ347pzX4c7nyH93TkxPj/PdnAAA9UbmHCUAwKAJKQCASkIKAKCSkAIAqCSkAAAqCSkAgEpCCgCgkpACAKj0/wG98LWHU66IEAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res_batch = []\n",
    "\n",
    "for bi in batch:\n",
    "\n",
    "    b = {}\n",
    "\n",
    "    if bi:\n",
    "        fl_keys = ['ts', 'lat', 'lon', 'hdg', 'alt', 'spd',\n",
    "                   'roc', 'ep_seg_b', 'lat_seg_b', 'lon_seg_b', 'lat_seg_e', 'lon_seg_e',\n",
    "                   'fl_seg_b', 'fl_seg_e', 'seq']\n",
    "\n",
    "        try:\n",
    "            fl1 = {}\n",
    "            for k in fl_keys:\n",
    "                fl1[k] = bi[\"%s%s\" % (k, '_1')]\n",
    "\n",
    "            try:\n",
    "                fl1 = crop_ddr2_flight_seg(fl1)\n",
    "            except Exception as e:\n",
    "                print('Cropping DDR2 flight failed, error: ')\n",
    "                print(e)\n",
    "                continue\n",
    "\n",
    "            try:\n",
    "                fl1 = add_waypoint_segments(fl1)\n",
    "                fl1 = fl1[fl1.wp_seg.notnull()]\n",
    "            except Exception as e:\n",
    "                print('Adding waypoints to flight failed, error: ')\n",
    "                print(e)\n",
    "                continue\n",
    "\n",
    "            if fl1 is None:\n",
    "                continue\n",
    "\n",
    "            if len(fl1) == 0:\n",
    "                continue\n",
    "\n",
    "            fl1['hdg_int'] = fl1.apply(lambda x: calc_compass_bearing(\n",
    "                                    (x['wp_seg'][2][0], x['wp_seg'][2][1]),\n",
    "                                    (x['wp_seg'][2][2], x['wp_seg'][2][3])),\n",
    "                                           axis=1)\n",
    "\n",
    "            fl2 = {}\n",
    "\n",
    "            for k in fl_keys:\n",
    "                fl2[k] = bi[\"%s%s\" % (k, '_2')]\n",
    "            \n",
    "            try:\n",
    "                fl2 = crop_ddr2_flight_seg(fl2)\n",
    "            except Exception as e:\n",
    "                print('Cropping DDR2 flight failed, error: ')\n",
    "                print(e)\n",
    "                continue\n",
    "\n",
    "            try:\n",
    "                fl2 = add_waypoint_segments(fl2)\n",
    "                fl2 = fl2[fl2.wp_seg.notnull()]\n",
    "            except Exception as e:\n",
    "                print('Adding waypoints to flight failed, error: ')\n",
    "                print(e)\n",
    "                continue\n",
    "\n",
    "            if fl2 is None:\n",
    "                continue\n",
    "\n",
    "            if len(fl2) == 0:\n",
    "                continue\n",
    "\n",
    "            fl2['hdg_int'] = fl2.apply(lambda x: calc_compass_bearing(\n",
    "                                            (x['wp_seg'][2][0], x['wp_seg'][2][1]),\n",
    "                                            (x['wp_seg'][2][2], x['wp_seg'][2][3])),\n",
    "                                        axis=1)\n",
    "\n",
    "            plt.figure(figsize=(10,10))\n",
    "            plt.scatter(fl1['lat'], fl1['lon'])\n",
    "            plt.scatter([i[2][0] for i in fl1['wp_seg']],[i[2][1] for i in fl1['wp_seg']])\n",
    "            plt.scatter([i[2][2] for i in fl1['wp_seg']],[i[2][3] for i in fl1['wp_seg']])\n",
    "            plt.scatter(fl2['lat'], fl2['lon'])\n",
    "            plt.scatter([i[2][0] for i in fl2['wp_seg']],[i[2][1] for i in fl2['wp_seg']])\n",
    "            plt.scatter([i[2][2] for i in fl2['wp_seg']],[i[2][3] for i in fl2['wp_seg']])\n",
    "            plt.show()\n",
    "\n",
    "        except Exception as e:\n",
    "            print('Preprocessing data failed, error:')\n",
    "            print(e)\n",
    "            continue\n",
    "\n",
    "# return res_batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>spd</th>\n",
       "      <th>hdg</th>\n",
       "      <th>wp_seg</th>\n",
       "      <th>hdg_int</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.59518</td>\n",
       "      <td>9.50592</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.31</td>\n",
       "      <td>(0, 5876.088641623721, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.59381</td>\n",
       "      <td>9.50342</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.31</td>\n",
       "      <td>(0, 5886.380487980794, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.58997</td>\n",
       "      <td>9.49647</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.31</td>\n",
       "      <td>(0, 5917.579555896321, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.58859</td>\n",
       "      <td>9.49405</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.31</td>\n",
       "      <td>(0, 5932.040234477679, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.58305</td>\n",
       "      <td>9.48411</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.22</td>\n",
       "      <td>(0, 5980.507214369075, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.57742</td>\n",
       "      <td>9.47388</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.22</td>\n",
       "      <td>(0, 6024.159075469537, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.54524</td>\n",
       "      <td>9.41625</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6305.5526408422975, (54.6466666666667, 9.4...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.54387</td>\n",
       "      <td>9.41375</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6315.432393912797, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.54140</td>\n",
       "      <td>9.40931</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6336.057211898556, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.54002</td>\n",
       "      <td>9.40688</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6349.702993215293, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.53022</td>\n",
       "      <td>9.38932</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6433.469842839095, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.52872</td>\n",
       "      <td>9.38661</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6445.3011510001215, (54.6466666666667, 9.4...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.52592</td>\n",
       "      <td>9.38168</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6472.7867957108665, (54.6466666666667, 9.4...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.52361</td>\n",
       "      <td>9.37750</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6490.663469800453, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.52082</td>\n",
       "      <td>9.37250</td>\n",
       "      <td>431.0</td>\n",
       "      <td>226.13</td>\n",
       "      <td>(0, 6514.264845298606, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.51560</td>\n",
       "      <td>9.36318</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.22</td>\n",
       "      <td>(0, 6559.770919759627, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.51421</td>\n",
       "      <td>9.36068</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.22</td>\n",
       "      <td>(0, 6571.090176330313, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.47209</td>\n",
       "      <td>9.28531</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.12</td>\n",
       "      <td>(0, 6924.946848023766, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.46314</td>\n",
       "      <td>9.26921</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.12</td>\n",
       "      <td>(0, 6995.187507309513, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.45895</td>\n",
       "      <td>9.26189</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.03</td>\n",
       "      <td>(0, 7037.122416777066, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.45744</td>\n",
       "      <td>9.25913</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.03</td>\n",
       "      <td>(0, 7047.036037479152, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.45607</td>\n",
       "      <td>9.25671</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.03</td>\n",
       "      <td>(0, 7059.58568532042, (54.6466666666667, 9.469...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.45453</td>\n",
       "      <td>9.25398</td>\n",
       "      <td>432.0</td>\n",
       "      <td>226.03</td>\n",
       "      <td>(0, 7073.267744200994, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.45026</td>\n",
       "      <td>9.24637</td>\n",
       "      <td>432.0</td>\n",
       "      <td>225.94</td>\n",
       "      <td>(0, 7109.415357966098, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.44899</td>\n",
       "      <td>9.24416</td>\n",
       "      <td>432.0</td>\n",
       "      <td>225.94</td>\n",
       "      <td>(0, 7122.411320714395, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.44637</td>\n",
       "      <td>9.23942</td>\n",
       "      <td>432.0</td>\n",
       "      <td>225.94</td>\n",
       "      <td>(0, 7141.52100102159, (54.6466666666667, 9.469...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.44205</td>\n",
       "      <td>9.23184</td>\n",
       "      <td>432.0</td>\n",
       "      <td>225.94</td>\n",
       "      <td>(0, 7182.938741952219, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.43204</td>\n",
       "      <td>9.21403</td>\n",
       "      <td>434.0</td>\n",
       "      <td>225.93</td>\n",
       "      <td>(0, 7268.040973865975, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.41711</td>\n",
       "      <td>9.18756</td>\n",
       "      <td>434.0</td>\n",
       "      <td>226.02</td>\n",
       "      <td>(0, 7397.860773309422, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1.525313e+09</td>\n",
       "      <td>54.41589</td>\n",
       "      <td>9.18540</td>\n",
       "      <td>434.0</td>\n",
       "      <td>226.02</td>\n",
       "      <td>(0, 7408.538203674948, (54.6466666666667, 9.46...</td>\n",
       "      <td>229.222609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.68468</td>\n",
       "      <td>5.78445</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 57769.55462166237, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.68266</td>\n",
       "      <td>5.78215</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 57787.121373509886, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.68129</td>\n",
       "      <td>5.78059</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 57799.02204159359, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.67945</td>\n",
       "      <td>5.77850</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57815.27364589918, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.67810</td>\n",
       "      <td>5.77698</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57827.91136622507, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.67657</td>\n",
       "      <td>5.77532</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57845.594761284476, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.67438</td>\n",
       "      <td>5.77278</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57862.08174243086, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.67270</td>\n",
       "      <td>5.77087</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57876.786915774304, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.67103</td>\n",
       "      <td>5.76897</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.04</td>\n",
       "      <td>(3, 57891.3212268045, (53.1641666666667, 6.666...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.66953</td>\n",
       "      <td>5.76730</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57906.33467687755, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.66783</td>\n",
       "      <td>5.76537</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57921.333484185445, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.66633</td>\n",
       "      <td>5.76370</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57936.330550888946, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.66481</td>\n",
       "      <td>5.76196</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57948.95316177387, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.66243</td>\n",
       "      <td>5.75929</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57971.63053448705, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.66078</td>\n",
       "      <td>5.75736</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 57983.09512652727, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.65758</td>\n",
       "      <td>5.75378</td>\n",
       "      <td>446.0</td>\n",
       "      <td>215.15</td>\n",
       "      <td>(3, 58014.06992192915, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.65590</td>\n",
       "      <td>5.75188</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58029.2150726879, (53.1641666666667, 6.666...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.65353</td>\n",
       "      <td>5.74921</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58051.12108640537, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.65287</td>\n",
       "      <td>5.74844</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58055.79493379594, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.65099</td>\n",
       "      <td>5.74630</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58071.96887071854, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.64934</td>\n",
       "      <td>5.74444</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58087.13262146702, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.64604</td>\n",
       "      <td>5.74073</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58117.970053728, (53.1641666666667, 6.6666...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.64408</td>\n",
       "      <td>5.73845</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58132.152348373245, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.64175</td>\n",
       "      <td>5.73586</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58155.473610043504, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.64077</td>\n",
       "      <td>5.73471</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58162.01350051259, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1001</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.63927</td>\n",
       "      <td>5.73301</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58175.25688030764, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.63757</td>\n",
       "      <td>5.73108</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58190.0772124046, (53.1641666666667, 6.666...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1003</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.63570</td>\n",
       "      <td>5.72899</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58208.14420274725, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1004</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.63402</td>\n",
       "      <td>5.72708</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58222.62385705623, (53.1641666666667, 6.66...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>1.525315e+09</td>\n",
       "      <td>51.63234</td>\n",
       "      <td>5.72517</td>\n",
       "      <td>445.0</td>\n",
       "      <td>215.22</td>\n",
       "      <td>(3, 58237.093691477196, (53.1641666666667, 6.6...</td>\n",
       "      <td>219.581104</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1004 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                ts       lat      lon    spd     hdg  \\\n",
       "0     1.525313e+09  54.59518  9.50592  432.0  226.31   \n",
       "1     1.525313e+09  54.59381  9.50342  432.0  226.31   \n",
       "2     1.525313e+09  54.58997  9.49647  432.0  226.31   \n",
       "3     1.525313e+09  54.58859  9.49405  432.0  226.31   \n",
       "4     1.525313e+09  54.58305  9.48411  432.0  226.22   \n",
       "5     1.525313e+09  54.57742  9.47388  432.0  226.22   \n",
       "6     1.525313e+09  54.54524  9.41625  431.0  226.13   \n",
       "7     1.525313e+09  54.54387  9.41375  431.0  226.13   \n",
       "8     1.525313e+09  54.54140  9.40931  431.0  226.13   \n",
       "9     1.525313e+09  54.54002  9.40688  431.0  226.13   \n",
       "10    1.525313e+09  54.53022  9.38932  431.0  226.13   \n",
       "11    1.525313e+09  54.52872  9.38661  431.0  226.13   \n",
       "12    1.525313e+09  54.52592  9.38168  431.0  226.13   \n",
       "13    1.525313e+09  54.52361  9.37750  431.0  226.13   \n",
       "14    1.525313e+09  54.52082  9.37250  431.0  226.13   \n",
       "15    1.525313e+09  54.51560  9.36318  432.0  226.22   \n",
       "16    1.525313e+09  54.51421  9.36068  432.0  226.22   \n",
       "17    1.525313e+09  54.47209  9.28531  432.0  226.12   \n",
       "18    1.525313e+09  54.46314  9.26921  432.0  226.12   \n",
       "19    1.525313e+09  54.45895  9.26189  432.0  226.03   \n",
       "20    1.525313e+09  54.45744  9.25913  432.0  226.03   \n",
       "21    1.525313e+09  54.45607  9.25671  432.0  226.03   \n",
       "22    1.525313e+09  54.45453  9.25398  432.0  226.03   \n",
       "23    1.525313e+09  54.45026  9.24637  432.0  225.94   \n",
       "24    1.525313e+09  54.44899  9.24416  432.0  225.94   \n",
       "25    1.525313e+09  54.44637  9.23942  432.0  225.94   \n",
       "26    1.525313e+09  54.44205  9.23184  432.0  225.94   \n",
       "27    1.525313e+09  54.43204  9.21403  434.0  225.93   \n",
       "28    1.525313e+09  54.41711  9.18756  434.0  226.02   \n",
       "29    1.525313e+09  54.41589  9.18540  434.0  226.02   \n",
       "...            ...       ...      ...    ...     ...   \n",
       "976   1.525315e+09  51.68468  5.78445  445.0  215.22   \n",
       "977   1.525315e+09  51.68266  5.78215  445.0  215.22   \n",
       "978   1.525315e+09  51.68129  5.78059  445.0  215.22   \n",
       "979   1.525315e+09  51.67945  5.77850  446.0  215.15   \n",
       "980   1.525315e+09  51.67810  5.77698  446.0  215.15   \n",
       "981   1.525315e+09  51.67657  5.77532  446.0  215.15   \n",
       "982   1.525315e+09  51.67438  5.77278  446.0  215.15   \n",
       "983   1.525315e+09  51.67270  5.77087  446.0  215.15   \n",
       "984   1.525315e+09  51.67103  5.76897  445.0  215.04   \n",
       "985   1.525315e+09  51.66953  5.76730  446.0  215.15   \n",
       "986   1.525315e+09  51.66783  5.76537  446.0  215.15   \n",
       "987   1.525315e+09  51.66633  5.76370  446.0  215.15   \n",
       "988   1.525315e+09  51.66481  5.76196  446.0  215.15   \n",
       "989   1.525315e+09  51.66243  5.75929  446.0  215.15   \n",
       "990   1.525315e+09  51.66078  5.75736  446.0  215.15   \n",
       "991   1.525315e+09  51.65758  5.75378  446.0  215.15   \n",
       "992   1.525315e+09  51.65590  5.75188  445.0  215.22   \n",
       "993   1.525315e+09  51.65353  5.74921  445.0  215.22   \n",
       "994   1.525315e+09  51.65287  5.74844  445.0  215.22   \n",
       "995   1.525315e+09  51.65099  5.74630  445.0  215.22   \n",
       "996   1.525315e+09  51.64934  5.74444  445.0  215.22   \n",
       "997   1.525315e+09  51.64604  5.74073  445.0  215.22   \n",
       "998   1.525315e+09  51.64408  5.73845  445.0  215.22   \n",
       "999   1.525315e+09  51.64175  5.73586  445.0  215.22   \n",
       "1000  1.525315e+09  51.64077  5.73471  445.0  215.22   \n",
       "1001  1.525315e+09  51.63927  5.73301  445.0  215.22   \n",
       "1002  1.525315e+09  51.63757  5.73108  445.0  215.22   \n",
       "1003  1.525315e+09  51.63570  5.72899  445.0  215.22   \n",
       "1004  1.525315e+09  51.63402  5.72708  445.0  215.22   \n",
       "1005  1.525315e+09  51.63234  5.72517  445.0  215.22   \n",
       "\n",
       "                                                 wp_seg     hdg_int  \n",
       "0     (0, 5876.088641623721, (54.6466666666667, 9.46...  229.222609  \n",
       "1     (0, 5886.380487980794, (54.6466666666667, 9.46...  229.222609  \n",
       "2     (0, 5917.579555896321, (54.6466666666667, 9.46...  229.222609  \n",
       "3     (0, 5932.040234477679, (54.6466666666667, 9.46...  229.222609  \n",
       "4     (0, 5980.507214369075, (54.6466666666667, 9.46...  229.222609  \n",
       "5     (0, 6024.159075469537, (54.6466666666667, 9.46...  229.222609  \n",
       "6     (0, 6305.5526408422975, (54.6466666666667, 9.4...  229.222609  \n",
       "7     (0, 6315.432393912797, (54.6466666666667, 9.46...  229.222609  \n",
       "8     (0, 6336.057211898556, (54.6466666666667, 9.46...  229.222609  \n",
       "9     (0, 6349.702993215293, (54.6466666666667, 9.46...  229.222609  \n",
       "10    (0, 6433.469842839095, (54.6466666666667, 9.46...  229.222609  \n",
       "11    (0, 6445.3011510001215, (54.6466666666667, 9.4...  229.222609  \n",
       "12    (0, 6472.7867957108665, (54.6466666666667, 9.4...  229.222609  \n",
       "13    (0, 6490.663469800453, (54.6466666666667, 9.46...  229.222609  \n",
       "14    (0, 6514.264845298606, (54.6466666666667, 9.46...  229.222609  \n",
       "15    (0, 6559.770919759627, (54.6466666666667, 9.46...  229.222609  \n",
       "16    (0, 6571.090176330313, (54.6466666666667, 9.46...  229.222609  \n",
       "17    (0, 6924.946848023766, (54.6466666666667, 9.46...  229.222609  \n",
       "18    (0, 6995.187507309513, (54.6466666666667, 9.46...  229.222609  \n",
       "19    (0, 7037.122416777066, (54.6466666666667, 9.46...  229.222609  \n",
       "20    (0, 7047.036037479152, (54.6466666666667, 9.46...  229.222609  \n",
       "21    (0, 7059.58568532042, (54.6466666666667, 9.469...  229.222609  \n",
       "22    (0, 7073.267744200994, (54.6466666666667, 9.46...  229.222609  \n",
       "23    (0, 7109.415357966098, (54.6466666666667, 9.46...  229.222609  \n",
       "24    (0, 7122.411320714395, (54.6466666666667, 9.46...  229.222609  \n",
       "25    (0, 7141.52100102159, (54.6466666666667, 9.469...  229.222609  \n",
       "26    (0, 7182.938741952219, (54.6466666666667, 9.46...  229.222609  \n",
       "27    (0, 7268.040973865975, (54.6466666666667, 9.46...  229.222609  \n",
       "28    (0, 7397.860773309422, (54.6466666666667, 9.46...  229.222609  \n",
       "29    (0, 7408.538203674948, (54.6466666666667, 9.46...  229.222609  \n",
       "...                                                 ...         ...  \n",
       "976   (3, 57769.55462166237, (53.1641666666667, 6.66...  219.581104  \n",
       "977   (3, 57787.121373509886, (53.1641666666667, 6.6...  219.581104  \n",
       "978   (3, 57799.02204159359, (53.1641666666667, 6.66...  219.581104  \n",
       "979   (3, 57815.27364589918, (53.1641666666667, 6.66...  219.581104  \n",
       "980   (3, 57827.91136622507, (53.1641666666667, 6.66...  219.581104  \n",
       "981   (3, 57845.594761284476, (53.1641666666667, 6.6...  219.581104  \n",
       "982   (3, 57862.08174243086, (53.1641666666667, 6.66...  219.581104  \n",
       "983   (3, 57876.786915774304, (53.1641666666667, 6.6...  219.581104  \n",
       "984   (3, 57891.3212268045, (53.1641666666667, 6.666...  219.581104  \n",
       "985   (3, 57906.33467687755, (53.1641666666667, 6.66...  219.581104  \n",
       "986   (3, 57921.333484185445, (53.1641666666667, 6.6...  219.581104  \n",
       "987   (3, 57936.330550888946, (53.1641666666667, 6.6...  219.581104  \n",
       "988   (3, 57948.95316177387, (53.1641666666667, 6.66...  219.581104  \n",
       "989   (3, 57971.63053448705, (53.1641666666667, 6.66...  219.581104  \n",
       "990   (3, 57983.09512652727, (53.1641666666667, 6.66...  219.581104  \n",
       "991   (3, 58014.06992192915, (53.1641666666667, 6.66...  219.581104  \n",
       "992   (3, 58029.2150726879, (53.1641666666667, 6.666...  219.581104  \n",
       "993   (3, 58051.12108640537, (53.1641666666667, 6.66...  219.581104  \n",
       "994   (3, 58055.79493379594, (53.1641666666667, 6.66...  219.581104  \n",
       "995   (3, 58071.96887071854, (53.1641666666667, 6.66...  219.581104  \n",
       "996   (3, 58087.13262146702, (53.1641666666667, 6.66...  219.581104  \n",
       "997   (3, 58117.970053728, (53.1641666666667, 6.6666...  219.581104  \n",
       "998   (3, 58132.152348373245, (53.1641666666667, 6.6...  219.581104  \n",
       "999   (3, 58155.473610043504, (53.1641666666667, 6.6...  219.581104  \n",
       "1000  (3, 58162.01350051259, (53.1641666666667, 6.66...  219.581104  \n",
       "1001  (3, 58175.25688030764, (53.1641666666667, 6.66...  219.581104  \n",
       "1002  (3, 58190.0772124046, (53.1641666666667, 6.666...  219.581104  \n",
       "1003  (3, 58208.14420274725, (53.1641666666667, 6.66...  219.581104  \n",
       "1004  (3, 58222.62385705623, (53.1641666666667, 6.66...  219.581104  \n",
       "1005  (3, 58237.093691477196, (53.1641666666667, 6.6...  219.581104  \n",
       "\n",
       "[1004 rows x 7 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fl2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bi = batch[10]\n",
    "b = {}\n",
    "\n",
    "if bi:\n",
    "    fl_keys = ['ts', 'lat', 'lon', 'hdg', 'alt', 'spd',\n",
    "               'roc', 'ep_seg_b', 'lat_seg_b', 'lon_seg_b',\n",
    "               'fl_seg_b', 'fl_seg_e', 'seq']\n",
    "\n",
    "    fl1 = {}\n",
    "    for k in fl_keys:\n",
    "        fl1[k] = bi[\"%s%s\" % (k, '_1')]\n",
    "    \n",
    "    first_ddr2_wp_1 = find_waypoint_index_v2((fl1['lat'][0],fl1['lon'][0]), list(zip(fl1['lat_seg_b'],fl1['lon_seg_b'])))\n",
    "    last_ddr2_wp_1 = find_waypoint_index_v2((fl1['lat'][-1],fl1['lon'][-1]), list(zip(fl1['lat_seg_b'],fl1['lon_seg_b'])))\n",
    "    \n",
    "    for kd in ['ep_seg_b', 'lat_seg_b', 'lon_seg_b','fl_seg_b', 'fl_seg_e', 'seq']:\n",
    "        fl1[kd] = fl1[kd][first_ddr2_wp_1:last_ddr2_wp_1+2]\n",
    "\n",
    "    fl2 = {}\n",
    "    for k2 in fl_keys:\n",
    "        fl2[k2] = bi[\"%s%s\" % (k2, '_2')]\n",
    "    \n",
    "    first_ddr2_wp_2 = find_waypoint_index_v2((fl2['lat'][0],fl2['lon'][0]), list(zip(fl2['lat_seg_b'],fl2['lon_seg_b'])))\n",
    "    last_ddr2_wp_2 = find_waypoint_index_v2((fl2['lat'][-1],fl2['lon'][-1]), list(zip(fl2['lat_seg_b'],fl2['lon_seg_b'])))\n",
    "    \n",
    "    for kd in ['ep_seg_b', 'lat_seg_b', 'lon_seg_b','fl_seg_b', 'fl_seg_e', 'seq']:\n",
    "        fl2[kd] = fl2[kd][first_ddr2_wp_2:last_ddr2_wp_2+2]\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(20,20))\n",
    "\n",
    "plt.scatter(list(fl1['lat']),list(fl1['lon']), c=\"b\", s=2)\n",
    "plt.scatter(fl1['lat'][0],fl1['lon'][0], c=\"b\", s=20)\n",
    "plt.scatter(fl1['lat_seg_b'][0],fl1['lon_seg_b'][0], c=\"b\", s=20)\n",
    "plt.plot(list(fl1['lat_seg_b']),list(fl1['lon_seg_b']))\n",
    "plt.scatter(list(fl2['lat']),list(fl2['lon']), c=\"r\", s=2)\n",
    "plt.scatter(fl2['lat'][0],fl2['lon'][0], c=\"b\", s=20)\n",
    "plt.plot(list(fl2['lat_seg_b']),list(fl2['lon_seg_b']))\n",
    "plt.scatter(fl2['lat_seg_b'][0],fl2['lon_seg_b'][0], c=\"b\", s=20)\n",
    "\n",
    "# plt.scatter(list(fl1['lon']),list(fl1['lat']), c=\"b\", s=2)\n",
    "# plt.scatter(fl1['lon'][0],fl1['lat'][0], c=\"b\", s=20)\n",
    "# plt.scatter(fl1['curr_lon'][0],fl1['curr_lat'][0], c=\"b\", s=20)\n",
    "# plt.plot(list(fl1['curr_lon']),list(fl1['curr_lat']))\n",
    "# plt.scatter(list(fl2['lon']),list(fl2['lat']), c=\"r\", s=2)\n",
    "# plt.scatter(fl2['lon'][0],fl2['lat'][0], c=\"b\", s=20)\n",
    "# plt.plot(list(fl2['curr_lon']),list(fl2['curr_lat']))\n",
    "# plt.scatter(fl2['curr_lon'][0],fl2['curr_lat'][0], c=\"b\", s=20)\n",
    "\n",
    "# plt.xlim(tuple(lon_bounds))\n",
    "# plt.ylim(tuple(lat_bounds))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "preprocessed_batch = preprocess_intent_conflicts(batch)\n",
    "\n",
    "ttc_est, ttc_act, ttca_bin, ttce_bin = process_flight_batch(preprocessed_batch)\n",
    "    \n",
    "perf_dict = create_performance_dict(ttc_act, ttc_est)\n",
    "\n",
    "# try:\n",
    "#                 for t in range(len(b['ts_1'])):\n",
    "\n",
    "#                         b['ttc'].append(b['ts_1'][-1] - b['ts_1'][t])\n",
    "#                         b['ettc'].append(ttc_est(fl1['lat'][t], fl1['lon'][t], fl2['lat'][t], fl2['lon'][t], \n",
    "#                                              fl1['hdg_int'][t], fl2['hdg_int'][t], fl1['spd'][t], fl2['spd'][t]))\n",
    "#                 b['ttc_diff'] = [x-y for x,y in zip(b['ttc'],b['ettc'])]\n",
    "#             except:\n",
    "#                 continue\n",
    "\n",
    "#             for tt in range(int(la_time/bin_sec)):\n",
    "#                 bmin = tt*bin_sec\n",
    "#                 bmax = (tt+1)*bin_sec\n",
    "#                 if str(bmax) not in list(bin_dp_df.keys()):\n",
    "#                     bin_dp_df[str(bmax)] = []\n",
    "\n",
    "#                 bin_dp_df[str(bmax)].extend([e for e,t in zip(b['ttc_diff'], b['ttc']) \n",
    "#                                                     if t >= bmin and t <= bmax])\n",
    "\n",
    "\n",
    "#             plt.plot(b['ttc'], b['ettc'])\n",
    "#     plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "perf_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "box_data = []\n",
    "\n",
    "bin_df = bin_dp_df\n",
    "\n",
    "for k in [kx for kx in bin_df.keys() if int(kx) <= 1200]:\n",
    "    box_data.append((int(k), [i for i in bin_df[k] if not np.isnan(i)]))\n",
    "    \n",
    "box_data_sort = sorted(box_data, key=lambda tup: tup[0])\n",
    "box_data_2 = [i[1] for i in box_data_sort]\n",
    "\n",
    "x = range(len(box_data_2))\n",
    "\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.boxplot(box_data_2, showfliers=False, patch_artist=True, whis=[5,95])\n",
    "plt.xticks(x, [i[0] for i in box_data_sort])\n",
    "plt.xticks(rotation=70)\n",
    "plt.xlabel('Look-ahead time (seconds)')\n",
    "plt.ylabel('TTC difference in seconds')\n",
    "plt.title('Evolution of TTC error over look-ahead time')\n",
    "plt.show()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_obj(bin_df,'intent_dict')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "def save_obj(obj, name ):\n",
    "    with open(name + '.pkl', 'wb') as f:\n",
    "        pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)\n",
    "\n",
    "def load_obj(name ):\n",
    "    with open(name + '.pkl', 'rb') as f:\n",
    "        return pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cur_read.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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